Oncologic outcomes after Total Mesometrial Resection (TMMR) or treatment according to current international guidelines in FIGO (2009) stages IB1-IIB cervical cancer: an observational cohort study

Summary Background According to international guidelines, standard treatment (ST) with curative intent in cervical cancer (CC) comprises radical hysterectomy and pelvic lymphadenectomy in early stages (International Federation of Gynecology and Obstetrics (FIGO) 2009 IB1, IIA1), adjuvant chemoradiation is recommended based on risk factors upon final pathology. Definitive chemoradiation is recommended in locally advanced stages (FIGO 2009 IB2, IIA2, IIB). Total mesometrial resection (TMMR) with therapeutic lymph node dissection (tLND) without adjuvant radiation has emerged as a promising treatment. Here we compare oncologic outcome by TMMR + tLND or ST. Methods In this observational cohort study, women treated according to international guidelines were identified in the population-based registries from Sweden and women treated with TMMR were identified in the Leipzig Mesometrial Resection (MMR) Study Database (DRKS 0001517) 2011–2020. Relevant clinical and tumour related variables were extracted. Recurrence-free survival (RFS) and overall survival (OS) by ST or TMMR was analysed with log-rank test, cumulative incidence function and proportional hazard regression yielding hazard ratios (HR) with 95% confidence intervals (CI), adjusted for relevant confounders. Findings Between 2011 and 2020, 1007 women were included in the final analysis. 733 women were treated according to ST and 274 with TMMR. RFS at five years was 77.9% (95% CI 74.3–81.1) and 82.6% (95% CI 77.2–86.9) for the ST and TMMR cohorts respectively (p = 0.053). In early-stage CC, RFS was higher after TMMR as compared to ST, 91.2% vs 81.8% (p = 0.002). In the adjusted analysis, TMMR was associated with a lower hazard of recurrence (HR 0.39; 95% CI 0.22–0.69) and death (HR 0.42; 95% CI 0.21–0.86) compared to ST. The absolute difference in risk of recurrence at 5 years was 9.4% (95% CI 3.2–15.7) in favor of TMMR. In locally advanced CC, no significant differences in RFS or OS was observed. Interpretation Compared to ST, TMMR without radiation therapy was associated with superior oncologic outcomes in women with early-stage cervical cancer whereas no difference was observed in locally advanced disease. Our findings together with previous evidence suggest that TMMR may be considered the primary option for both early-stage and locally advanced cervical cancer confined to the Müllerian compartment. Funding This study was supported by grants from Centre for Clinical Research Sörmland (Sweden) and Region Stockholm (Sweden).


Supplementary appendix
Oncologic outcomes after Total Mesometrial Resection (TMMR) or treatment according to current international guidelines in FIGO (2009) stages IB1-IIB cervical cancer: an observational cohort study

Table of contents
Table 1 Crude survival estimates and absolute risk differences between TMMR and ST    Adjusted landmark estimates of the association between TMMR and ST and time to different failures.

Figure 1
Oncologic outcomes by surgical approach in the Swedish cohort All patients 2011-2020: Adjusted estimates of the association between TMMR and Standard treatment and time to different failures.Competing risk regression (Fine and Gray) or proportional hazards regression (Cox): sHR/HR, 95% CI and Wald p-values.Treatment reference category= Standard.E= Total number of events.CE= Total number of competing events.Table 3a.All patients Event FAIL (any event): Control of confounding by regression, propensity score or inverse probability weights.Proportional hazards regression (Cox): HR, 95%CI.Treatment reference category = Standard.Confounders: age, year of treatment, stage, histology, positive lymph nodes and tumor size.UNADJ= Only treatment included in the regression model (crude effect).REGR= Confounders included in the regression model.PS= Confounders included in the regression model as quintiles of the propensity score.IPW= Confounders included using inverse probability weights and included in the regression model as weights.Table 3b.All patients Event 1 st local recurrence: Control of confounding by regression, propensity score or inverse probability weights.Proportional hazards regression (Cox): HR, 95%CI.Treatment reference category = Standard.Confounders: age, year of treatment, stage, histology, positive lymph nodes and tumor size.UNADJ= Only treatment included in the regression model (crude effect).REGR= Confounders included in the regression model.PS= Confounders included in the regression model as quintiles of the propensity score.IPW= Confounders included using inverse probability weights and included in the regression model as weights.Table 3c.All patients Event 1 st distant recurrence: Control of confounding by regression, propensity score or inverse probability weights.Proportional hazards regression (Cox): HR, 95%CI.Treatment reference category = Standard.Confounders: age, year of treatment, stage, histology, positive lymph nodes and tumor size.UNADJ= Only treatment included in the regression model (crude effect).REGR= Confounders included in the regression model.PS= Confounders included in the regression model as quintiles of the propensity score.IPW= Confounders included using inverse probability weights and included in the regression model as weights.Table 3d.All patients Event 1 st DEATH: Control of confounding by regression, propensity score or inverse probability weights.Proportional hazards regression (Cox): HR, 95%CI.Treatment reference category = Standard.Confounders: age, year of treatment, stage, histology, positive lymph nodes and tumor size.UNADJ= Only treatment included in the regression model (crude effect).REGR= Confounders included in the regression model.PS= Confounders included in the regression model as quintiles of the propensity score.IPW= Confounders included using inverse probability weights and included in the regression model as weights.Table 3e.All patients Event DEATH: Control of confounding by regression, propensity score or inverse probability weights.Proportional hazards regression (Cox): HR, 95%CI.Treatment reference category = Standard.Confounders: age, year of treatment, stage, histology, positive lymph nodes and tumor size.UNADJ= Only treatment included in the regression model (crude effect).REGR= Confounders included in the regression model.PS= Confounders included in the regression model as quintiles of the propensity score.IPW= Confounders included using inverse probability weights and included in the regression model as weights.Table 4. Locally advanced stage patients 2011-2020: Adjusted landmark (+180 days) estimates of the association between country and time to different failures.Competing risk regression (Fine and Gray) or proportional hazards regression (Cox)): sHR/HR, 95%CI and Wald p-values.Reference category = Standard treatment E= Total number of events.CE= Total number of competing events.All patients alive and recurrence-free at landmark (180 days).Adjusted for age, year of treatment, stage, histology, positive lymph nodes and tumor size.

Figure 1
Figure 1 RFS and OS in women with early-stage (FIGO* IB1, IIA1) cervical cancer in the Swedish cohort, by minimally invasive surgery or laparotomy Blue line: Abdominal surgery.Red line: Minimally invasive surgery.FIGO=International Federation of Gynecology and Obstetrics; *Staging according to International Federation of Obstetrics and Gynecology, FIGO, 2009 staging manual

Table 2
Multivariate analysis of confounders in Cox regression modelsTable 3aControl of confounding by regression, propensity score or inverse probability weights for any eventTable 3bControl of confounding by regression, propensity score or inverse probability weights for 1 st event local recurrence

Table 3c Control
of confounding by regression, propensity score or inverse probability weights for 1 st event distant recurrence

Table 3d Control
of confounding by regression, propensity score or inverse probability weights for 1 st event deathTable 3eControl of confounding by regression, propensity score or inverse probability weights for death